Lead Data Architect, Product Analytics

Meta; San Francisco (CA); On-site; USD 177,000 - 247,000; Full time

Job summary

Meta is seeking a Data Engineer to shape data for billions of users and businesses across its family of apps. You will design scalable data solutions, collaborate with multiple teams, and deliver insights through robust data models and visualizations.

You will drive governance and security, mentor peers, and influence product and strategy with data-driven storytelling. The role emphasizes building efficient ETL pipelines, improving logging, and aligning data products with company goals.

Qualifications

• Bachelor’s degree or equivalent practical experience in CS/Engineering.
• 7+ years in data roles (engineer, analyst, or scientist) with data focus.
• Strong SQL, ETL, data modeling and programming in Python/Scala/Java.

Responsibilities

• Own data architecture for large-scale projects and tradeoffs.
• Improve logging frameworks and triage data infrastructure issues.
• Collaborate with engineers, PMs and data scientists; visualize insights.
• Define SLAs for datasets and ensure governance and security.
• Design and launch data models and visualizations for multiple use cases.
• Tackle data integration challenges with efficient ETL patterns.
• Optimize pipelines, dashboards, and development workflows.
• Mentor teammates and promote data-driven decision making.

Skills

Data architecture

Data modeling

ETL design

SQL

Python

Data visualization

Communication storytelling

Mentoring

Security governance

Cross-functional collaboration

Education

Bachelor's degree in CS/Engineering

Master's or PhD preferred

Tools

Airflow

Spark

BigQuery / Dataflow

Cloud platforms

Job description

Meta is seeking a Data Engineer to shape data for billions of users and businesses across its family of apps. You will design scalable data solutions, collaborate with multiple teams, and deliver insights through robust data models and visualizations.

You will drive governance and security, mentor peers, and influence product and strategy with data-driven storytelling. The role emphasizes building efficient ETL pipelines, improving logging, and aligning data products with company goals.